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The use of low doses of radium-224 (224Ra) chloride for the treatment of ankylosing spondylitis was stopped following the discovery that patients treated with it had a higher than control incidence of leukaemia and other cancers. This was so even though the treatment resulted in decreased pain and increased mobility-both of which are associated with decreased mortality. It was decided to re-analyze the epidemiological data looking at all causes of death. The risk of leukaemia, solid cancer, death from non-cancer causes and from all causes in a study populations of men that received either the typical dose of 5.6 to 11.1 MBq of 224Ra, any dose of 224Ra or no radium were compared using the Cox proportional hazard model. For patients that received the typical dose of 224Ra agreed with the excess cancer was similar to that reported in previous studies. In contrast, these patients were less likely to die from non-cancer diseases and from all causes of death than the control patients. No excess mortality was also found in the population of all males that received the radionuclide. It is concluded that 224Ra treatment administered at low doses to patients with ankylosing spondylitis did not impact mortality from all causes. The study demonstrates the need to consider all causes of death and longevity when assessing health impacts following irradiation., Competing Interests: The authors have declared that no competing interests exist.

Purpose: Estimating cancer risks for continuous radiation exposures based upon data from acute exposures has been an important public health problem. A dose and dose rate effectiveness factor (DDREF) is typically used to estimate cancer risks for chronic exposures based upon risk estimates from acute exposures. A value of 2 for a DDREF has most often been used as proposed by the ICRP in ICRP60; however, an influential analysis of several cohorts concluded that there is no risk difference between acute and chronic exposures. It is the purpose of this article to analyze the recent nuclear worker studies and estimate the dose rate effectiveness factor, DREF, for solid cancers., Materials and Methods: Twelve mortality studies were identified each with at least 100 cancer deaths and a meta-analysis was then carried out using their individual ratio of low dose rate cancer effect (LDR) to the corresponding high dose rate effect from the A-bomb cohort (LSS). The ratio is denoted by Q and its reciprocal is then an estimate of the DREF., Results: The result was Q= 0.36 (95% CI = 0.11, 0.60) and DREF = 2.63 (95% confidence interval [CI] = 1.61, 7.14). Clearly, this estimate is more consistent with a DREF of 2 than with a DREF of 1. The difficulty with the estimate Q = 0.36 is that it is driven by only two large and dissimilar worker studies, the INWORKS study (q 1  = 1.14) and the Mayak worker cohort (q 3  = 0.30). The higher exposures for these nuclear workers were often in the early years (e.g. before 1960) with exposures from neutrons and internal emitters that are not included in the risk analyses resulting in likely overestimation of cancer effects per dose which would increase the estimate of the DREF. The Mayak study did, however, adjust for plutonium exposures. Finally, consideration is given to other cohort studies where DREF values may possibly be determined, such as the environmental exposures to the Techa River area residents and the Chernobyl cleanup workers as well as medical X-ray workers. Although dissimilar an overall meta-analysis yielded a Q = 0.45 (95% CI = 0.24, 0.66)., Conclusions: It is concluded that the best estimate of a DREF is still about 2. However, because of the various problems with the epidemiology studies, especially their dosimetry, it is concluded that a DREF of about 2 should be accepted with considerable caution since it is driven solely by the Mayak study.

Purpose: This review evaluates the role of dose rate on cell and molecular responses. It focuses on the influence of dose rate on key events in critical pathways in the development of cancer. This approach is similar to that used by the U.S. EPA and others to evaluate risk from chemicals. It provides a mechanistic method to account for the influence of the dose rate from low-LET radiation, especially in the low-dose region on cancer risk assessment. Molecular, cellular, and tissues changes are observed in many key events and change as a function of dose rate. The magnitude and direction of change can be used to help establish an appropriate dose rate effectiveness factor (DREF)., Conclusions: Extensive data on key events suggest that exposure to low dose-rates are less effective in producing changes than high dose rates. Most of these data at the molecular and cellular level support a large (2-30) DREF. In addition, some evidence suggests that doses delivered at a low dose rate decrease damage to levels below that observed in the controls. However, there are some data human and mechanistic data that support a dose-rate effectiveness factor of 1. In summary, a review of the available molecular, cellular and tissue data indicates that not only is dose rate an important variable in understanding radiation risk but it also supports the selection of a DREF greater than one as currently recommended by ICRP ( 2007 ) and BEIR VII (NRC/NAS 2006 ).

Background In 2002 the International Agency for Research on Cancer classified extremely low frequency magnetic fields (ELFMF) as a possible carcinogen on the basis of epidemiological evidence. Experimental bioassays on rats and mice performed up to now on ELFMF alone or in association with known carcinogens have failed to provide conclusive confirmation. Objectives To study the carcinogenic effects of combined exposure to sinusoidal-50 Hz (S-50 Hz) magnetic fields and acute γ radiation in Sprague-Dawley rats. Methods We studied groups of male and female Sprague-Dawley rats exposed from prenatal life until natural death to 20 or 1000 μT S-50 Hz MF and also to 0.1 Gy γ radiation delivered as a single acute exposure at 6 weeks of age. Results The results of the study showed significant carcinogenic effects for the mammary gland in males and females and a significant increased incidence of malignant schwannomas of the heart as well as increased incidence of lymphomas/leukemias in males. Conclusions These results call for a re-evaluation of the safety of non-ionizing radiation.

Radiation cancer risk estimates have been based primarily on the atomic bomb survivor cohorts, which involve an acute exposure. To adjust for lower dose and continuous exposures, a dose and dose rate effectiveness factor (DDREF) is applied to the acute risk estimates. The commonly accepted value for the DDREF at 1 Gy by the ICRP and the NCRP has been 2. BEIR VII changed this by estimating the value to be 1.5 including an uncertainty distribution. The BEIR VII committee used the atomic bomb solid cancer incidence data to make this estimation, and they chose to truncate the data at 1.5 Gy. The Committee also used the Oak Ridge mouse studies and estimated a DDREF based on these data. Finally they used the animal data-derived DDREF distribution as a Bayesian prior distribution for the atomic bomb survivor DDREF distribution and used the posterior distribution as their DDREF result. The resulting distribution had a maximum likelihood estimate of 1.4, and the Committee chose 1.5 as their best estimate. The purpose of this paper is to reexamine the BEIR VII analysis of both the atomic bomb survivor data and the mouse data. Based upon this analysis, the author concludes that changing the DDREF from 2 to 1.5 is not justified.

Purpose: To determine the relative toxicity of alpha- and beta-radiations under conditions of controlled temporal and spatial dose distribution., Methods: Fused aluminosilicate particles were radiolabelled with either (45)Ca (a beta-emitter) or (242)Cm (an alpha-emitter). These were injected into CBA/Ca mice to give lifespan, whole-body doses of approximately 0.5, 1.0 or 1.5 Gy. Most animals were entered into a lifespan toxicity study, but some were killed for radiochemical analysis and autoradiography., Results: Twenty-seven tumour types were identified. The most common malignant tumours were: Mammary carcinoma; liver carcinoma; malignant lymphoma; uterine histiocytic sarcoma. Excess relative risk (strictly hazard ratio) was higher for radiation-induced carcinomas than for sarcomas. The carcinomas, but not sarcomas showed a reduction in relative risk at the highest radiation dose employed. This reduction was most easily attributed to a systemic effect. The highest relative toxicity measured was for liver carcinoma (5.9, 95% confidence intervals [CI] 2.4, 14) and the lowest for uterine carcinoma (0.6, CI 0.03, 9.7). Overall, the excess relative risk ratio for SURVIVAL WAS 1.9 (CI 1.1, 3.2), FOR ALL CARCINOMA WAS 2.3 (CI 1.7, 3.0) AND FOR ALL SARCOMA WAS 2.7 (CI 0.72, 10)., Conclusions: The 10-fold variability in the observed toxicity ratio for different tumour endpoints shows that tissue sensitivity is a more important determinant of relative toxicity than radiation quality. The use of single radiation-weighting (w(R)) factors for radiation risk prediction and for radiological protection dosimetry is inconsistent with scientific observation.

The Mayak Production Association (MPA) worker registry has shown evidence of plutonium-induced health effects. Workers were potentially exposed to plutonium nitrate [(239)Pu(NO(3))(4)] and plutonium dioxide ((239)PuO(2)). Studies of plutonium-induced health effects in animal models can complement human studies by providing more specific data than is possible in human observational studies. Lung, liver, and bone cancer mortality rate ratios in the MPA worker cohort were compared to those seen in beagle dogs, and models of the excess relative risk of lung, liver, and bone cancer mortality from the MPA worker cohort were applied to data from life-span studies of beagle dogs. The lung cancer mortality rate ratios in beagle dogs are similar to those seen in the MPA worker cohort. At cumulative doses less than 3 Gy, the liver cancer mortality rate ratios in the MPA worker cohort are statistically similar to those in beagle dogs. Bone cancer mortality only occurred in MPA workers with doses over 10 Gy. In dogs given (239)Pu, the adjusted excess relative risk of lung cancer mortality per Gy was 1.32 (95% CI 0.56-3.22). The liver cancer mortality adjusted excess relative risk per Gy was 55.3 (95% CI 23.0-133.1). The adjusted excess relative risk of bone cancer mortality per Gy(2) was 1,482 (95% CI 566.0-5686). Models of lung cancer mortality based on MPA worker data with additional covariates adequately described the beagle dog data, while the liver and bone cancer models were less successful.

Determination of radiation protection guidelines for persons working with plutonium has been complicated by limited human data on the biological behavior and subsequent health effects from internally deposited plutonium. One solution has been the use of animal models to predict likely health effects in humans. To compare the relationships between plutonium inhalation and lung fibrosis and lung cancer, data from life-span studies of beagle dogs given a single exposure to either plutonium-238 dioxide (238PuO2) or plutonium-239 dioxide (239PuO2) were analyzed. Estimates of the cumulative hazard of lung fibrosis and lung cancer after exposure to either were generated. The hazard of lung fibrosis was not consistent with a linear no-threshold model, although the magnitude of the threshold differed by radionuclide. In dogs given 239PuO2, the best model of lung fibrosis incorporated a linear dose-response function; a linear-quadratic dose-response function fit the data better in dogs given 238PuO2. At any given cumulative dose, the lung fibrosis hazard was greater for dogs given 238PuO2. In dogs given 238PuO2, with or without covariates, a quadratic dose-response function for lung cancer hazard fit better than a linear no-threshold model. In dogs given 239PuO2, models of lung cancer with the dose-response function as the sole predictor variable were consistent with a linear no-threshold model; however, a quadratic dose-response function with a cell-killing term fit better. These findings have implications for radiation protection because, while lung cancer hazard was dependent on cumulative dose, regardless of isotope, the lung fibrosis hazard depended on both cumulative dose and isotope.

Generalized relative and absolute risk models are fitted to the latest Japanese atomic bomb survivor solid cancer and leukemia mortality data (through 2000), with the latest (DS02) dosimetry, by classical (regression calibration) and Bayesian techniques, taking account of errors in dose estimates and other uncertainties. Linear-quadratic and linear-quadratic-exponential models are fitted and used to assess risks for contemporary populations of China, Japan, Puerto Rico, the U.S. and the UK. Many of these models are the same as or very similar to models used in the UNSCEAR 2006 report. For a test dose of 0.1 Sv, the solid cancer mortality for a UK population using the generalized linear-quadratic relative risk model is estimated as 5.4% Sv(-1) [90% Bayesian credible interval (BCI) 3.1, 8.0]. At 0.1 Sv, leukemia mortality for a UK population using the generalized linear-quadratic relative risk model is estimated as 0.50% Sv(-1) (90% BCI 0.11, 0.97). Risk estimates varied little between populations; at 0.1 Sv the central estimates ranged from 3.7 to 5.4% Sv(-1) for solid cancers and from 0.4 to 0.6% Sv(-1) for leukemia. Analyses using regression calibration techniques yield central estimates of risk very similar to those for the Bayesian approach. The central estimates of population risk were similar for the generalized absolute risk model and the relative risk model. Linear-quadratic-exponential models predict lower risks (at least at low test doses) and appear to fit as well, although for other (theoretical) reasons we favor the simpler linear-quadratic models.

Approximately 1800 female CBA/Ca mice were exposed by inhalation at three dose levels to beta particles from (45)Ca-labeled fused aluminosilicate particles (FAP), to alpha particles from (242)Cm-labeled FAP, or to carrier control FAP. Another group of mice inhaled no FAP and were designated as untreated cage controls. The FAP in combination with these radionuclides was used to achieve the same spatial and temporal distribution of alpha- and beta-particle dose within the irradiated mice. Some mice were killed to determine the clearance of radiolabeled FAP from their lungs, and the remainder were allocated to a life-span study. All animals were subjected to a detailed necropsy. To facilitate the identification of small tumors, the lungs were rendered transparent in methyl salicylate and examined under back illumination for the presence of lesions. Lung nodules and other microscopic lesions were excised for histological examination. The median survival of mice in all groups was approximately 910 days. The control animals lived longer than those that were irradiated, but it was difficult to determine a dose-response relationship for survival among the exposed mice. Benign adenomas and, less frequently, malignant adenocarcinomas were identified in all animal groups. The prevalence of these tumors was approximately 28.8% in the control mice, which is consistent with the results of other studies using the same strain of mouse. After exposure to radionuclide-labeled FAP, there was a significant dose-related increase in the prevalence of lung tumors in (242)Cm- (peak prevalence 55%) and (45)Ca-exposed (peak prevalence 48.6%) mice. The prevalence of tumors in the mice that received (242)Cm-labeled FAP was approximately twice that in the mice that inhaled (45)Ca-labeled FAP within the range of doses employed (0.55-4.69 Gy). Using the ratio of the slope of the linear component of the dose-response curves, the toxicity of the alpha particles relative to the beta particles was 1.5 (90% CI: 0.7, 9.0) for all adenomas and 9.4 (90% CI: 5.0, 23.0) for the less frequent adenocarcinomas. The relative toxicity for adenocarcinomas was found to decrease with increasing dose.

The large United States county-based study () in which an inverse relationship has been suggested between residential low-dose radon levels and lung cancer mortality has been reviewed. While this study has been used to evaluate the validity of the linear nonthreshold theory, the grouped nature of its data limits the usefulness of this application. Our assessment of the study's approach, including a reanalysis of its data, also indicates that the likelihood of strong, undetected confounding effects by cigarette smoking, coupled with approximations of data values and uncertainties in accuracy of data sources regarding levels of radon exposure and intensity of smoking, compromises the study's analytic power. The most clear data for estimating lung cancer risk from low levels of radon exposure continue to rest with higher-dose studies of miner populations in which projections to zero dose are consistent with estimates arising from most case-control studies regarding residential exposure.

Cancer incidence and mortality data from the cohort of Japanese atomic bomb survivors in Hiroshima have been adjusted for the uncertainty that exists in the dose estimates, the systematic error in the neutron dose estimates, and a dose-dependent relative biological effectiveness. Once the adjustments were incorporated in the dose estimates, the data were modeled with a threshold term to allow for the possibility of a threshold dose response. The dose response models that were fit to the data were otherwise the same models used in the original papers. The threshold term was included in the model allowing for possible threshold values ranging from 0 to 0.35 Sv. These analyses suggest that the fit of the A-bomb solid tumor and leukemia incidence data are significantly improved by the addition of a threshold term in comparison with the purely linear or linear quadratic model. The results from the mortality data suggest that the leukemia data agree more with the threshold model than the linear quadratic model although the linear quadratic model is statistically equivalent, while the solid tumor data does not suggest any improvement with a threshold.

Radiation cancer risks are typically determined by the use of simple statistical descriptions of epidemiological data. It is important in risk assessment in general, however, to attempt to incorporate as much biological information into the risk models as possible. We illustrate this by presenting a biologically-based linear-quadratic-exponential (LQE) incidence rate model for radiation-induced chronic myeloid leukemia (CML). The model consists of a linear-quadratic dose-response for the induction of BCR-ABL, a waiting time distribution between BCR-ABL formation and detection of CML, and an exponential cell-killing term that multiplies both the background and induced incidence rates. Using data exclusive of the A-bomb survivor cohort, Bayesian priors are defined for each of the nine parameters in this LQE model. The priors are based on chromosomal translocations in lymphocytes, hematopoietic stem cell survival experiments, CML waiting times in women irradiated for benign disease, the background CML incidence rate in the U.S. population, and genomic DNA target sizes of BCR and ABL. Fixing three of the LQE model parameters to the means of their priors, maximum likelihood estimates of the remaining six parameters were obtained using A-bomb survivor incidence data for Hiroshima males. The likelihood estimates and the corresponding six prior distributions, both approximated as multivariate normal, were then used to form Bayesian posteriors for the six parameters not fixed. With these posteriors the LQE model yields Qgamma*=0.0042 Gy(-1) where Qgamma* is the upper 95% confidence bound of the lifetime CML risk per person-gray in the limit of low doses of gamma-rays. This value is slightly less than Qgamma*=0.0049 Gy(-1) obtained from likelihood estimates of the LQE parameters, and substantially less than Qgamma*=0.0158 Gy(-1) obtained for a simple statistical model linear in dose for kermas less than 4 Gy.

Cancer incidence and mortality data from the atomic bomb survivors cohort has been analyzed to allow for the possibility of a threshold dose response. The same dose-response models as used in the original papers were fit to the data. The estimated cancer incidence from the fitted models over-predicted the observed cancer incidence in the lowest exposure group. This is consistent with a threshold or non-linear dose-response at low-doses. Thresholds were added to the dose-response models and the range of possible thresholds is shown for both solid tumor cancers as well as the different leukemia types. This analysis suggests that the A-bomb cancer incidence data agree more with a threshold or non-linear dose-response model than a purely linear model although the linear model is statistically equivalent. This observation is not found with the mortality data. For both the incidence data and the mortality data the addition of a threshold term significantly improves the fit to the linear or linear-quadratic dose response for both total leukemias and also for the leukemia subtypes of ALL, AML, and CML.

Ionizing radiation long has been recognized as a cause of cancer. Among environmental cancer risks, radiation is unique in the variety of organs and tissues that it can affect. Numerous epidemiological studies with good dosimetry provide the basis for cancer risk estimation, including quantitative information derived from observed dose-response relationships. The amount of cancer attributable to ionizing radiation is difficult to estimate, but numbers such as 1 to 3% have been suggested. Some radiation-induced cancers attributable to naturally occurring exposures, such as cosmic and terrestrial radiation, are not preventable. The major natural radiation exposure, radon, can often be reduced, especially in the home, but not entirely eliminated. Medical use of radiation constitutes the other main category of exposure; because of the importance of its benefits to one's health, the appropriate prevention strategy is to simply work to minimize exposures.

In this paper we combine Japanese data on radiation exposure and cancer mortality with U.S. data on cancer incidence and lethality to estimate the effects of ionizing radiation on cancer incidence. The analysis is based on the mathematical relationship between the mortality rate and the incidence and lethality rates, as well as on statistical models that relate Japanese incidence rates to U.S. incidence rates and radiation risk factors. Our approach assumes that the risk of death from causes other than the cancer does not depend on whether or not the cancer is present, and among individuals with the cancer, the risk of death attributable to the cancer is the same in Japan and the U.S. and is not affected by radiation exposure. In particular, we focus on the incidence of breast cancer in Japanese women and how this incidence is affected by radiation risk factors. The analysis uses Japanese exposure and mortality data from the Radiation Effects Research Foundation study of atomic bomb survivors and U.S. incidence and lethality data from the Surveillance, Epidemiology, and End Results Registry. Even without Japanese incidence data, we obtain reasonable estimates of the incidence of breast cancer in unexposed Japanese women and identify the radiation risk factors that affect this incidence. Our analysis demonstrates that the age at exposure is an important risk factor, but that the incidence of breast cancer is not affected by the city of residence (Nagasaki versus Hiroshima) or the time since exposure.

Cancer risk models and their relationship to ionizing radiation are discussed. There are many model assumptions and risk factors that have a large quantitative impact on the cancer risk estimates. Other health end points such as mental retardation may be an even more serious risk than cancer for those with in utero exposures.

Risk estimation in radiation carcinogenesis depends primarily on epidemiological data and hazard rate models. The A-bomb survivors follow-up provides information on the complexity of this process. Several hazard rate models are briefly discussed and illustrated using the A-bomb experience.